Adopting a Pragmatic Approach to Data Management

In the journey toward becoming a data-driven organisation, adopting a structured approach to data management is crucial. We see more and more companies accepting this advice and considering the next steps in their data journey. However, we also notice that many data managers find the prospect of a structured approach daunting. When not handled correctly, it can cause significant delays in deliveries, and the reality is that data teams cannot simply pause their operations to figure everything out first and establish the necessary frameworks. So, how can you prevent ending up with a spaghetti of solutions while keeping your momentum of deliveries?

The Importance of Pragmatism

Everything starts with pragmatism, an important word that is often underrated. Adopting a structured approach should in no case mean that you need to think about every single detail of your approach; keep it agile, while continuing your business as usual.

Next are 3 areas you could focus on towards a structured data approach:

Invest in Good Policies:

Develop comprehensive policies early on. These policies should guide initial decisions and evolve with the organisation’s needs. Policies are not just documents but living guidelines that help in maintaining data quality, security, and compliance. Here are a few critical policies:

Data Access Policy: Defines who can access data and under what circumstances, ensuring proper permissions and security.
Data Security Policy: Details measures to secure data against unauthorized access, breaches, and loss.
Data Quality Policy: Establishes standards and procedures for maintaining data quality, including validation and cleaning processes.
Data Retention and Disposal Policy: Specifies how long data should be kept and methods for safe disposal once it’s no longer needed.

These policies need regular updates and clear communication to ensure everyone in the organisation understands and adheres to them. Regular training sessions and workshops can be effective in embedding these policies into the organisational culture.

Define Ready and Done:

Establish clear definitions of “ready” and “done” for all new developments. This ensures that projects progress in the right direction and meet established criteria before moving forward. The concept of “ready” might include having all necessary data requirements met, while “done” ensures that the deliverables meet quality standards and business needs. Clear definitions help in:

Ensuring Consistency: All team members understand and follow the same standards.
Improving Efficiency: Projects can be completed faster and with fewer errors when everyone knows the requirements.
Facilitating Communication: Clear terms reduce misunderstandings between technical and non-technical stakeholders.

Implementing these definitions might involve creating checklists or templates that can be used across projects, ensuring uniformity and thoroughness.

Focus on Value Delivery:

Approach each case with a focus on delivering value. Prioritise initiatives that offer the greatest impact and ensure they align with the overarching data strategy, even if this strategy is only a simple vision at the beginning. Go for that low-hanging fruit that will give your team and delivery a boost at the start and go from there. The most important thing is that you are taking steps forward instead of staying stationary. Here are some tips to maintain focus on value:

Identify Key Metrics: Determine what metrics will best measure success and focus on improving them.
Engage Stakeholders: Regularly involve business stakeholders to ensure that the data initiatives are aligned with business goals.
Iterate Quickly: Start with small, achievable goals that can deliver quick wins and build momentum.

By following these guidelines, organisations can navigate the complexities of data management while maintaining continuous operations. This structured approach not only facilitates smoother transitions but also ensures that the data initiatives are aligned with business goals, ultimately driving value and innovation.